With the development of the Internet, increasingly more services can be implemented by using the Internet, for example, electronic commerce, social networking, or even banking services. In view of authenticity and security, users usually need to upload some entity information for entity verification. For example, the entity information can include location information, name information, real scene images, etc. For example, verify entity information of a physical store that is provided by a merchant, and verify entity information of a company that is provided by a user.
In the existing technology, location information and real scene images in entity information are usually verified through human review, for example, manually review location information and store images of a physical store that are provided by a merchant. For another example, manually review location information and company images of a company that are provided by a user.
However, in the real world, location information and real scene images are complex and variable, authenticity of location information and real scene images of each entity cannot be verified one by one through human review, and verification can only be subjectively performed based on experience. In addition, forgery of location information and real scene images is very simple, which causes great interference to human review. Therefore, the solution in the existing technology that entity information is verified through human review based on a combination of location information and real scene images is characterized by very low accuracy. In addition, human review is limited by working hours and manpower, and it is difficult to continuously guarantee timeliness.